For the third task above, following RotNet method [1]}, given an unlabeled image, we rotate it using a rotation angle randomly chosen from the list \(\lbrace 0^{\circ }, 90^{\circ }, 180^{\circ }, 270^{\circ }\rbrace \) , and then define its corresponding label to be the rotated angle (1 out of 4 possibilities). Then, we input rotated images to the network and optimize it to detect the rotation angle using the cross entropy loss function.
